1. Field of the Invention
The present invention relates to the management of information handling systems. More specifically, embodiments of the invention provide a system, method, and computer-readable medium for using predictive web analytics to optimize the effectiveness of a website.
2. Description of the Related Art
As the value and use of information continues to increase, individuals and businesses seek additional ways to process and store information. One option available to users is information handling systems. An information handling system generally processes, compiles, stores, and/or communicates information or data for business, personal, or other purposes thereby allowing users to take advantage of the value of the information. Because technology and information handling needs and requirements vary between different users or applications, information handling systems may also vary regarding what information is handled, how the information is handled, how much information is processed, stored, or communicated, and how quickly and efficiently the information may be processed, stored, or communicated. The variations in information handling systems allow for information handling systems to be general or configured for a specific user or specific use such as financial transaction processing, airline reservations, enterprise data storage, or global communications. In addition, information handling systems may include a variety of hardware and software components that may be configured to process, store, and communicate information and may include one or more computer systems, data storage systems, and networking systems.
These same information handling systems have played a key role in the rapid growth of electronic commerce on the Internet. One known aspect of electronic commerce is web analytics, which includes the measurement, collection, analysis and reporting of Internet data for purposes of understanding and optimizing web usage. In general, web analytics falls into two broad categories. The first, off-site web analytics, refers to the measurement of a target website's audience (e.g., opportunity), share of voice (e.g., visibility), and buzz (e.g., user comments) that is happening on the Internet as a whole. The second, on-site web analytics, refers to the measure a visitor's behavior at a target website. This behavior includes the user's drivers and purchase conversions in a commercial context. The data resulting from such on-site web analytics is typically compared against key performance indicators (KPIs) for performance, and is also used to improve the web site or the response from a marketing campaign. As such, web analytics can be a key component in ensuring that the company's web presence is driving the results it desires, including brand reputation, revenue, self-support, sales leads, etc.
Historically, web analytics has typically been based upon observed results with clear test case protocols, which includes A/B style testing where different versions of the same web page are served up and then measured to see which version results in higher click-through rates, purchase conversion, and so forth. However, such approaches generally require the creation of multiple test cases. Furthermore, analysts often find themselves relying upon their intuition when deciding which features should be developed for testing. Moreover, the number of tests that can be conducted is typically limited due to the time it takes to run each test individually or in combination with other tests. As a result, the accuracy and reliability of traditional web analytics approaches can prove to be limited.